The text auto-encoder consists of an encoder and decoder for automatically generating a compressed vector representation for the caption as illustrated in Fig. REF . The LSTM encoder-decoder adopts the sequence-to-sequence structure similar to neural machine translation [1]}.
In the text auto-encoder, the encoder module reads the input caption \(\mathbf {S} = \lbrace S_1, ..., S_N\rbrace \) , and encodes it to a fixed-length vector \(u_g\in \mathbb {R}^{d_e}\) . The LSTM is commonly used such that:
\(h_t &= f_1(S_t, h_{t-1}, c_{t-1}),\\u_g &= h_N,\) 
